Foot-and-mouth disease (FMD) can cause large disruptive epidemics in livestock. Current eradication measures rely on the rapid clinical detection and removal of infected herds. Here, we evaluated the potential for preclinical diagnosis during reactive surveillance to reduce the risk of between-farm transmission. We used data from transmission experiments in cattle where both samples from indivi...

during 2007 – 2008 different fruit gardens in shiraz (fars province, iran) were surveyed for samples being collected from infected apple, pear and quince trees. symptoms of the infected trees included water soaking of infected tissue, wilt and tissue necrosis, scorched and blackend of blossom bracts or young shoots. a total of 47 strains were isolated from infected trees using na medium. on the...

We use a natural ordered extension of the Chinese Restaurant Process to grow a two-parameter family of binary self-similar continuum fragmentation trees. We provide an explicit embedding of Ford’s sequence of alpha model trees in the continuum tree which we identified in a previous article as a distributional scaling limit of Ford’s trees. In general, the Markov branching trees induced by the t...

background and objectives: oleaceae family contains approximately 20 species of small trees and ancient world of the mediterranean, north africa, southeast asia, north to southern china, scotland and east australia have a wide dispersion. they are evergreen and have small leaves that are integrated have been met and the fruit is drup. olive trees resistant to drought and adapt to poor soils and...

We use a natural ordered extension of the Chinese Restaurant Process to grow a two-parameter family of binary self-similar continuum fragmentation trees. We provide an explicit embedding of Ford’s sequence of alpha model trees in the continuum tree which we identified in a previous article as a distributional scaling limit of Ford’s trees. In general, the Markov branching trees induced by the t...

The selection of feature subspaces for growing decision trees is a key step in building random forest models. However, the common approach using randomly sampling a few features in the subspace is not suitable for high dimensional data consisting of thousands of features, because such data often contains many features which are uninformative to classification, and the random sampling often does...